Senior Analyst, Supply Chain Analytics EU
Amazon
Luxembourg, LU
il y a 6j

Have you ever ordered a product on Amazon websites and when the box arrived wondered how you got it so fast, how much it would have cost Amazon, and what kinds of systems & processes must be running behind the scenes to power the whole operation?

If so, the Europe Supply Chain Analytics team is for you.

Amazon seeks a passionate, results-oriented, analyst to join our European Supply Chain team in Luxembourg. You will be responsible to monitor and optimize our complex and expanding fulfilment network end-to-end.

Successful candidates will have the attitude of a data detective combined with strong analytic skills and problem solving mindset.

You will work both bottom up from anecdotes up to algorithmic improvements or top down from performance metrics monitoring down to processes improvements.

This highly visible role requires collaborating with software developers and product managers, retail, fulfillment centers, and transportation teams.

You must have the experience and capability to create and present documentation for senior executives. You love solving complex problems but you are equally strong at simplifying them for a less technical audience.

Your responsibilities include :

Identify the biggest opportunities to optimize forecasting, inventory placement, customer shipments, or inventory transfers

Lead complex analysis, develop models and reports to drive key strategic decisions.

Identify opportunities to deliver step-changes in supply chain performance through optimization of configurations and parameters, or through improved algorithms and processes.

Collaborate with operations, retai,l and software teams to implement key strategic initiatives.

Analyze financial impacts and prioritize new features based on their relevance.

Research, evaluate and roll-out software, tools or process improvements.

Track the realized savings and impacts, and communicate results to senior leaders.

BASIC QUALIFICATIONS

At least 4 years of professional experience in quantitative analytics or business intelligence.

Bachelor degree in engineering, operations research, mathematics, statistics, or other quantitative areas such as computer science or physics.

Knowledge of SQL. Mathematical, analytical, and data-driven decision making skills.

Experience with statistical analysis tools (such as R), root cause analysis, process design and control.

Excellent Microsoft Office skills, including strong working knowledge of Excel and VBA.

Excellent written and verbal communication skills. Ability to simplify complex topics for broad audiences. The role requires effective communication with colleagues from computer science, operations research and business backgrounds.

Team player with proven ability to work with cross-functional teams in various locations.

A track record of problem solving and creativity in finding / designing new solutions and innovative methods, using software systems and the desire to create and build new processes.

Ability to handle multiple competing priorities and projects in a fast-paced environment.

PREFERRED QUALIFICATIONS

Master’s degree in engineering, operations research, mathematics, statistics, or other quantitative areas such as computer science or physics.

Experience with scripting languages (Python, Perl, or Ruby) and UNIX.

Experience with analyzing big data sets (tables with 100M+ rows and thousands of columns are standard)

Experience working effectively with software engineering teams. Technical aptitude and familiarity with the design and use of software systems.

Familiarity with supply chain management concepts - forecasting, planning, optimization, logistics - gained through work experience or graduate level education.

Familiarity with statistical concepts and advanced statistical techniques - distributions, confidence intervals, time series analysis, regression models, clustering, machine learning

Familiarity with mathematical modelling & simulation techniques probability, optimization (linear programming, etc.), graph theory, state models

Familiarity with Big Data concepts and platforms (Hadoop, Mahout, etc.)

About our rewards

We'll expect you to go the extra mile, but we'll also make sure you're well rewarded. As well as a competitive salary, stock units and site performance-related pay potential, we offer a whole host of other benefits, including an employee discount.

Additionally, you will find yourself in a stimulating environment where you can develop processes as well as yourself as an individual by working with some of the best and brightest minds in the industry.

Our rapidly growing organization offers also many opportunities for building a diverse and rewarding career.

Make History

Amazon.com, a Fortune 500 company based in Seattle, Washington, opened on the World Wide Web in July 1995 and today offers Earth’s Biggest Selection.

Since Jeff Bezos started Amazon.com, we have significantly expanded our product offerings, international sites, and worldwide network of fulfilment and customer service centres.

Today, Amazon.com offers everything from books and electronics to tennis rackets and diamond jewellery. We operate sites in the United Kingdom, Germany, France, Japan, Canada, Italy, Spain and China (Joyo.

com) and maintain over 80 fulfilment centres around the world which encompass more than 26 million square feet.

If you thrive in a challenging and fast-paced environment, you’ll meet your match with us, as you will be part of a vibe of constant improvement, where the things you do at one moment, you will not necessarily be doing 6 months later.

We don’t like to sit still, which is why we always treat every day like the first day. A day to make more good things happen for our customers.

It’s that kind of spirit that drives our success now and keeps us ahead of the competition in the future. And you could be part of it.

It’s as simple as this : Work Hard. Have Fun. Make History.

Sound interesting? We wait for your application.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success.

We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.

By submitting your resume and application information, you authorize Amazon to transmit and store your information in the Amazon group of companies' world-wide recruitment database, and to circulate that information as necessary for the purpose of evaluating your qualifications for this or other job vacancies.

At least 4 years of professional experience in quantitative analytics or business intelligence.

Bachelor degree in engineering, operations research, mathematics, statistics, or other quantitative areas such as computer science or physics.

Knowledge of SQL. Mathematical, analytical, and data-driven decision making skills.

Experience with statistical analysis tools (such as R), root cause analysis, process design and control.

Excellent Microsoft Office skills, including strong working knowledge of Excel and VBA.

Excellent written and verbal communication skills. Ability to simplify complex topics for broad audiences. The role requires effective communication with colleagues from computer science, operations research and business backgrounds.

Team player with proven ability to work with cross-functional teams in various locations.

A track record of problem solving and creativity in finding / designing new solutions and innovative methods, using software systems and the desire to create and build new processes.

Ability to handle multiple competing priorities and projects in a fast-paced environment.

Master’s degree in engineering, operations research, mathematics, statistics, or other quantitative areas such as computer science or physics.

Experience with scripting languages (Python, Perl, or Ruby) and UNIX.

Experience with analyzing big data sets (tables with 100M+ rows and thousands of columns are standard)

Experience working effectively with software engineering teams. Technical aptitude and familiarity with the design and use of software systems.

Familiarity with supply chain management concepts - forecasting, planning, optimization, logistics - gained through work experience or graduate level education.

Familiarity with statistical concepts and advanced statistical techniques - distributions, confidence intervals, time series analysis, regression models, clustering, machine learning

Familiarity with mathematical modelling & simulation techniques probability, optimization (linear programming, etc.), graph theory, state models

Familiarity with Big Data concepts and platforms (Hadoop, Mahout, etc.)

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